What problem does it solve? After a coding session, it is hard to know why the AI agent struggled—slow file navigation, missing automated checks, or bloated steering files. This Skill runs a structured retrospective on a session and turns those friction points into concrete improvements for the agent's environment. ## Core Features & Use Cases - Session Log Analysis: Reads primary sources and session logs to reconstruct what actually happened during a run. - Seven Improvement Categories: Evaluates navigation, automated checks, coding standards, global AGENTS.md, tool economy, no-op instructions, and information access. - Severity-Ranked Findings: Presents candidate improvements ordered by severity so you can act on the highest-impact items first. - Use Case: After an agent repeatedly failed lint checks that CI never ran, invoke a retrospective to discover the repo has no guardrail wired up and get a recommendation to add a pre-commit hook or CI job. ## Quick Start Ask the agent to run a retrospective on the current coding session and suggest environment improvements.